SWOT Analysis of Lending Platform from Blockchain ...

103 | International Journal of Informatics Information System and Computer Engineering 4 (1) (2019) 103-116

SWOT Analysis of Lending Platform from Blockchain

Technology Perspectives

Wisnu Uriawan

INSA Lyon, LIRIS, UMR5205, France

Department of Informatics, UIN Sunan Gunung Djati Bandung, Indonesia

Correspondence: E-mail: [email protected], [email protected]

A B S T R A C T S A R T I C L E I N F O

Blockchain Technology become phenomenal issue in the world, emerging with bitcoin and IoT. It had been implemented in many areas in human activity. Advantages of blockchain technology is distributed ledger where resources distributed to all member in network. Loans or credit as part of human activity in their life. When we need cash for a major expense, it might be tempting to borrow from a payday lender or max out a credit card or similar, but you have other options that will not harm your credit or put you in a cycle of debt, even if your credit record is not all that great. Collateral loans could be a way to borrow the money as you need. One of which is the lending platform. Blockchain technology has been implemented in many lending platforms, but there are still any weaknesses that can be refined and optimized. Tool of analysis is SWOT, describes of four analysis, as follow: Strength, Weakness, Opportunity and Threats. This paper purpose to analyzed lending platform measured by look for the weaknesses variable and how to optimize that system performance that can improve for helping people in lending process. In addition, the result of this analysis can use for enhancement recommendation the system based on the weaknesses are found and opportunity for make a lending platform robust.

Article History: Received 18 Nov 2020 Revised 20 Nov 2020 Accepted 25 Nov 2020 Available online 26 Dec 2020 Available online 09 Sep 2018

___________________ Keywords: Blockchain, Distributed Ledger, Lending Platform, SWOT, Enhancement, Robust.

International Journal of Informatics, Information System and Computer

Engineering

Journal homepage: http://ejournal.upi.edu/index.php/ijost/

International Journal of Informatics Information System and Computer Engineering 4 (1) (2019) 103-116

W Uriawan. – SWOT Analysis of Lending Platform from Blockchain Technology Perspectives |104

1. INTRODUCTION

Blockchain arise in good time, it introduced with Bitcoin emerging in financial crisis in 2008 (G. Verdian, P. Tasca, C. Paterson, and G. Mondelli,, 2018), at the same time people need some money for survive in life. Traditional lender burdened people with high interest and more long-time payback period. Another way, individual can propose lending to traditional financial services, like a bank or financial institutions (I. González-Carrasco, J. L. Jiménez-Márquez, J. L. López-Cuadrado, and B. Ruiz-Mezcua,2019), but it’s very difficult for accepted because they should give some collateral. On the other hand, people do not have collateral for proposed some credit to financial institutions, more big proposed loans, will more collateral also (W. Presthus and N. O. O’Malley,2017). Financial institutions make some conditions for grading lending, it depend on the risk. High risk will high conditions and more collateral required. Blockchain has completed by technology modern for support in lending platform environment with the simple way and faster in processing (I. Anagnostopoulos,2018). Ledger will support for recorded all transactions on network with unique privilege it is work as individual or organization as well as (J. Li, D. Greenwood, and M. Kassem,2019). Smart contracts are supported to manage transactions with particular process with high code security and robustness with solidity adaptive language (W. Viriyasitavat and D. Hoonsopon,, 2019), peer-to-peer (P2P) lending is possible for person transaction with another person online

with simple way, in several country has successful apply that system as like in China and United Kingdom, its method provides for Small Medium Enterprises (SMEs) and individual with population increasing about 110% in year 2015-2016 and still developing for lending industry market with high risk (Y. Zhang, H. Li, M. Hai, J. Li, and A. Li, 2017), trustworthiness will help the transaction more faster because will reduced many following conditions like transaction credit record, collateral, many person rejected when applied lending or credit with small collateral ( C. R. Macaulay 2015), ( T. Yu and W. Shen 2019). According to the Transparency Market Research, lending market cap will growth in 2024 about $897.85 then before in 2015 about $26.16 billion (B. Bilbao and V. Argentaria, 2018) is significant and interesting for lending platform development in the future.

All the kind of services will provide with blockchain technology for financial institutions non-bank. Peer-to-peer networking a set group computer or network that can resource sharing by itself autonomous, without central authority need support by consensus. Asymmetric cryptography used for ensure the user can accesses the system and avoidance from malicious access or unauthority users, with this cryptography model only priviledge and authentic user can access the system (J. Chen and S. Micali, 2019). Cryptographic hashing merkle tree data structure is used to record all transactions from large datasets with unique authority so that data integrity is well maintained (L. Wang, X. Shen, J. Li, J. Shao, and Y. Yang, 2019). SWOT analysis identify several factors of


organizational or system for adapted and analyze present conditions for competitive advantages. Strength will identify positive value of the current process, weakness it shown vulnerability or error of the current system according to process after organizational evaluated. Opportunity use for identifying in the future beside competitive advantages. Threats is how the system can avoidance or minimized the risk today and in the Future (S. S. Humaidan, 2015), SWOT analysis will help the organization for manage better all the situation and conditions occurs also for increasing competitive advantages. This paper describes how to analyze the lending platform by looking for particularly the weaknesses and opportunity, that can improve the lending platform performance. In addition, weaknesses show the system leak or vulnerable so that the organization can fix this weakness become lending platform strength and robust.

2. METHODOLOGY

Blockchain is a coherent data structure

as a digital sign and becomes an

identity, then shared and distributed as

a database that contains a well-

structured log of transaction and

chronological information. The

database is called a ledger which

contains many transactions that have

occurred, user logging and data

maintenance. Transactions in the

general ledger will be collected into a

block, which is recorded with a time

stamp and cryptographically linked to

the genesis block that forms and

composes a sequence of events or other

blocks as a unit. The structure itself

describes the data structure, is a form of

digital consensus and is also used in

literature, algorithms or application

domains that are built on the design

block structure (M. Andoni et al, 2019),

(J. Mattila et al, 2016), (G. Wood, 2014).

Data transmission, sharing of

resources, and computing are all part of

computer networks. Cryptocurrency as

a distributed network resource to

others with a specific address. The

challenge is that the system needs to

ensure that the expenses that are

distributed do not double. A traditional

transaction such as bank and non-bank,

which acts as a mediator between a

third party and a trusted data storage

medium, will become a valid ledger

block and keep the data up to date.

Authority activated if several parties

need to write in the ledger at the same

time with concurrency control and

consolidation. The current centralized

management may not accept this,

because it is high cost and requires the

trust of network users to a third party

to operate the system (M. Andoni et al,

2019), (J. Mattila et al, 2016).

2.1 Ledger

A copy of the distributed ledger

will be the same held by all users on the

network. Consensus will add new data

every time there is a change to the

ledger if all users agree and the data is

valid. Any attempt to change the data

by one user then the other users will be

informed of the change, it creates

immutability (S. Pearson et al, 2019).

The genesis block is the place where

transactions are stored, and all blocks


will be cryptographically linked to each

other which records the data. The

nodes in the graph represent

transactions and their edges will show

the direction of confirmation between

transactions (B. Shala, U. Trick, A.

Lehmann, B. Ghita, and S. Shiaeles,

2019).

2.2 Fintech

The Financial Technologies (FinTech)

and the IoT (I. Anagnostopoulos, 2018),

(B. Shala, U. Trick, A. Lehmann, B.

Ghita, and S. Shiaeles, 2019), ( J. L.

Ferrer-Gomila, M. Francisca Hinarejos,

and A. P. Isern-Deyà, 2019). Although

both domains require the basic

common features of a decentralized

trusted transaction ledger, substantial

differences can be found in usage

principles, transaction volume and

rates, tight security requirements or

transaction fees. At FinTech, the main

challenge is ensuring highly secure and

reliable financial payments, with a low

volume of transaction failures and

some tolerance for transaction delays.

On the other hand, in IoT, using

multiple devices and a greater volume

of transactions is expected, with micro

and nano payments required for IoT

assets and data changes. Transaction

costs are a relevant issue here, as well

as transaction delays required for near

real-time operations (M. Pustišek and

A. Kos, 2018), shown by Fig. 1.

Fig. 1. Lending Process

2.3 Ethereum

Ethereum is a blockchain network with an open system. Ethereum and Bitcoin are tools that make it possible to bring the economic system into the software, complete with an account management system and a native exchange unit system for funneling through accounts (L. Catania, S. Grassi, and F. Ravazzolo, 2019). Games like Monopoly or something identic. Each player calls a native unit of coins for this exchange, token, or cryptocurrency, but it is no different from tokens on any other system: they are a form of money (or scripts) that can only be used in that system (C. Dannen, 2017).

Ethereum is a global transaction-based machine: it starts with block genesis and gradually executes transactions to manipulate it into final blocks. The last block is canonical Ethereum. Genesis blocks available in it such as account balance information, track records, reliable, real-world data and information; otherwise, anything that could be manipulated by the computer would be accepted. Transaction validation between blocks is essential to avoid invalid fake blocks or valid blocks undergoing changes. Invalid block changes will reduce the account balance without the same


renewal and opposite increases elsewhere. Valid block transitions generated by transactions (U. Team, 2018).

Decentralized protocols and applications, distributed storage, distributed shared marketplace and other concepts have the potential to enhance the computing industry and the support provided for peer-to-peer protocols for lending platforms. Writing code in Ethereum, will get a lot of blockchain functionality like a programming language completely useful for generating smart contracts functionality and more secure by arbitrary encoding and users can modify according to the objective (B. V. Buterin, 2009).

2.4 Smart Contract

The assigned and delegated smart contracts will execute the correct input. Distributed ledger is a distributed database of transaction history that is approved by the majority of participants in its network through a predetermined consensus mechanism. All participants in the network have a copy of the same ledger. Any changes in the ledger will be reflected in all on the final copy. Assets that are recorded in the ledger can be financial, legal, physical, electronic, or many other properties. Depending on the network rules, the ledger can be updated by some or all the participants. Major security and consensus issues are generally resolved through cryptographic mechanisms (A. Raschendorfer et al, 2019). Smart contracts are computer programs that enforce rules without requiring a third party. In the Bitcoin blockchain, basic versions of smart contracts are implemented through a writing system which can facilitate use cases such as

multi-user accounts, multi wallets, digital signatures and other services (M. Westerkamp, F. Victor, A. Küpper, and A. Kupper, 2019).

The security risks associated with

blockchain platforms and technology

are as follows: 1) It is difficult to

implement regulations to avoid money

laundering activities due to the high

level of anonymity using the protocol.

2) There are several cryptocurrencies

that have been indicated to be used for

money laundering purposes and are a

challenge ahead to enforce financial

penalties. 3) The ineffective tax

regulation scheme may be a side effect

of the anonymity factor. 4) Many

countries have introduced tax

regulations for cryptocurrencies, in an

effort to deal with the global

cryptocurrency phenomenon and

avoid risks for users who are exposed

to cryptocurrency price volatility. 5) In

the future, there will be problems of

inflation and risks of monetary and

financial stability, including the

potential loss of control over the

amount of currency to be circulated, the

level of risk will increase from the

cryptocurrency market and increased

credit in the economy with the use of

cryptocurrencies that are difficult to

control. 6) The emergence of the use of

cryptocurrency will be accompanied by

a series of new problems that arise with

regard to laws and regulations, so that

it can affect public confidence in

conventional currencies.

Cryptocurrency is like a representation

of value transactions, can be traded and

function generally as money (D. Unal,


M. Hammoudeh, and M. S. Kiraz,

2019).

Society of Worldwide Interbank

Financial Telecommunication (SWIFT)

system uses predefined code to pass on

transaction details through the SWIFT

network. Each transaction is described

by a series of SWIFT code. The code

consists of several key identifier

components, such as institution code,

country code, location code and branch

code to indicate the sender and receiver

(T. Qiu, R. Zhang, and Y. Gao, 2019).

SWOT analysis it contains about

relation identification of strengths,

weakness, opportunities and threats

from subject research. Strength contra

with weakness, opportunity versus

threats. Strength will identify about

resources available and running well,

Weakness for measure how high the

risks. Opportunity analyze represent

the marketplaces as the subject, while

threats is for prevent or minimize the

risk ( T. Qiu, R. Zhang, and Y. Gao,

2015), ( J. R. Glass, G. H. Kruse, and S.

A. Miller, 2015), ( H. Thamrin and E. W.

Pamungkas, 2017), ( A. Aich and S. K.

Ghosh, 2016). Identifying the lists of

positive and negative contribution

objectives with the subject evaluation.

SWOT analysis is required for the

selection of right method and

application, is very simple but the

result is better, and the

recommendation can use for next

process.

3. RESULTS AND DISCUSSION

Blockchain has become famous and is present for all daily activities in the fields of economy, business, education, health, and other non-bank financial institutions. Exponential growth has almost changed the world and provides more options for efficiency and low costs. The lending activity is an interesting area because many people have experiences at least once in their life. In practice of lending system, someone will become a lender and another party will be a borrower. There are many terms and conditions for this loan activity, including: collateral, ability to payback, trust, and the purpose of the loan. Blockchain technology will bridge these activities to reduce transaction times and complicated mechanisms. In the traditional lending process, it will take at least 1 week to a month, but borrowers cannot wait longer because of urgent needs.

3.1. Analysis Lending Platform

Smart contracts in blockchain technology have been used to replace a faster and more efficient lending process, one example of changing from centralization to a process of decentralization, trust, efficiency and accountability. One of the Spanish multinational banking groups Banco Bilbao Vizcaya Argentaria (BBVA) invested around € 75 million in corporate loans and has taken advantage of the distributed ledger and became the first international bank to implement blockchain technology .SWOT analysis for lending platform variable are blockchain technology, No mediator/Collateral, Competitive Rates, Reduced Risk, Improved


Efficiency, Market Cap and Competitive Advantages. SWOT analysis framework summarized

(B.Bilbao and V. Argentaria, 2018), (T. Qiu, R. Zhang, and Y. Gao, 2019) in the following Table 1.

Table 1. SWOT Analysis Framework

Variable Strengths Weakness Opportunitie

s Threats

Blockchain Technology √

No Mediator/ Collateral

√

Competitive Rates √

Trustiness √

Reduced Risk √

Improve Efficiency √

Market Cap √

Competitive Advantages

√

The lending platform will help

individuals who are looking for a place

to apply for loans or credit directly to

lenders. This process will reduce

dependence on financial institutions

such as banks and third parties.

Blockchain technology adopts the

traditional lending process by reducing

waste and making decisions quickly.

Illustration "if someone needs a loan or

credit, they just visit one of the loan

platforms and try to propose an

amount of credit need, then the system

will response with status of accepted or

rejected" in just a few minutes.

Blockchain technology is helping for

better and more profitable transactions

such as: safer, simpler operations,

generating potential passive income,

and people are starting to focus on

blockchain development.

Some loan platforms offer

convenience to use, but they require a

lot of terms and conditions. However,

it is still a burden for users, if the

lending platform still requires

collateral, users will have difficulty

fulfilling it so that users will still be

rejected. Finally, they tried to return to

traditional loans.

Investment in a lending platform is very interesting as long as it is completed with new technology that allow it to meet with the user experience and needs, many lending platforms only focus on profit without thinking about the user needs. Lending platforms offer the lending products but do not focus on user needs analysis so that will affect the success of a lending platform.

3.2. Analysis Lending Platform

Current lending platforms able to implement of blockchain technology through third parties, Bitcoin and Ethereum. Referring to the SWOT analysis shown in Table 2.


Bitcoin has a limitation that the bitcoin network will be a threat to future lending platforms and is quite difficult to develop. Ethereum is still open to development, therefore it is easier to develop and will grow faster without worrying about restrictions. Third parties, it is easier to start installing because they are developed by third parties, but it will be high cost and also requires third party maintenance. Mix (Bitcoin and Ethereum), the opportunity is open to take the lower to upper segment

classes, but the system is more complex to handle both transactions.

3.3. Trustworthiness

The most important thing about the lending platform is the level of trust, if the community has given trust, the lending platform will grow faster and have a good influence so that it will be recommended to other users. The best practices of each user will be to transfer his experience, refer to Table 3 below.

Ease of use describe how far lending platform have acceptance from users without complaint and satisfy in use.

Track Record Acceptance, statistical record acceptance and succeed for lending process. Member complaint,


s Threats

Bitcoin √

Ethereum √

Third-Party √

Mix (Bitcoin and Ethereum)

√

Bitcoin √

Ethereum √

Third-Party √

Mix (Bitcoin and Ethereum)

√


s Threats

Ease of use √

Track Record Acceptance

√

Member Complaint √

Time needed √

Market Capital √

Table 2. SWOT Technology Platform

Framework

Table 3. SWOT of Trustness


reduction or minimize of member complaint will indicate the good process. Time needed, how long lending process will need processing time, time that's shown can cut down complex process. Market Capital, how big market penetration of lending platform, larger

coverage area will bring trustiness to users.

3.4. Improved Efficiency

Efficiency is a keyword of the lending platform performance parameters will show in the Table 4 below.

Ratio of use, lending platform usability will describe the overall system performance. Comparison of Lenders and Borrowers, providing statistical data between Lenders and Borrowers so that users will learn the comparison of the two and see future trends. Asset vs Market, the lending platform must be able to present the asset report and market capitalization to the public, the user will study and analyze the results, for example, the asset must be greater than the market capitalization to guarantee the user's investment. Optimized technology,

the loan platform must always update the system periodically to keep all transactions up and running efficiently. Accumulation of errors, to minimize errors, is the obligation of the loan platform to ensure the system runs well with zero errors.

3.5. Market Capital

Each lending platform will competitive with many lending platforms in the world, they should prepare variable in Table 5 below.


s Threats

Ratio of use √

Comparative of Lender and Borrower

√

Asset vs Market √

Technology Optimized √

Error Accumulation √


s Threats

Performance √

Speed √

Technology driven √

Security √

Table 4. SWOT of Improve Efficiency

Table 5. SWOT of Competitive Advantages


Performance, the lending platform must have a good performance to be the winner or the best choice for the user. Speed is an indicator to measure how fast each transaction can be handled and measure the success of the transaction process. Driven by technology, the latest technological innovations will help improve performance and in line with the system architecture, the more recent technology uses will affect the lending platform's adaptability to the latest

technology. Security, a classic problem but very important to apply to the lending platform, a good system must have a high level of security, because it will be accessed by many users.

3.6. Competitive Advantages

Growth of lending platform shown by market capital, variables of market capital refers to Table 6 below.

Coverage area, how big is the coverage area of the lending platform that will be supported, the wider area will give opportunity to win the market with the risk of being more complex in managing the system. Kind of Country, the type of user will be influenced by the type of the state and shows the behavior of the user, the system must be able to handle all the behavior of users who access. Market

segmentation will show the user segment environment, middle to upper or lower class will be used as evaluation for market segmentation, corporate or personal trends will also measure the level of communication of the lending platform. Lending variants, lending platform products that are available in various variants and segmentations can open a wider market.

3.7. Comparative of Lending Platform

Comparative of lending platform will describe how performance their system

was built and how the system can handle many transactions with many products are offer refers to Table 7 below.


s Threats

Coverage area √

Kind of Country √

Market Segment √

Variant of lending √

Table 6. SWOT of Market Capital


4. CONCLUSION

The blockchain technology of the lending platform will affect the overall system performance, SWOT analysis variables show 6 Strengths, 5 Weaknesses, 6 Opportunities and 5 Threats. All variables describe how to manage the lending platform at the best possible performance. These recommendations will help in the future to develop a better lending platform and system maintenance

considering the Strengths and Opportunities, Weaknesses and Threats variables. However, for the best lending platform, focus on weaknesses and threats to make the system more reliable.

5. ACKNOWLEDGEMENTS

Authors wishing to acknowledge LIRIS UMR5205 Laboratory at INSA Lyon France and MORA Scholarship from Indonesian Government that

Variable Strength Weakness Opportunity Threats

Blockchain Technology

Bitcoin √

Ethereum √

Third-Party √

Mix (Bitcoin and Ethereum) √

Reduced Risk

Easy of use √

Track Record Acceptance √

Member complaint √

Time needed √

Market capital √

Improve Efficiency

Ratio of use

Comparative of

√

Lender and Borrower √

Asset vs Market √

Technology Optimized √

Error Handle √

Technology Optimized

Coverage area √

Kind of Country √

Market Segment √

Variant of lending √

Error Accumulation

Performance √

Speed √

Technology driven √

Security √

Table 7. SWOT of Competitive Advantages


supports and funds this research publication.

REFERENCES

Aich, A., & Ghosh, S. K. (2016). Application of SWOT analysis for the selection of technology for processing and disposal of MSW. Procedia Environmental Sciences, 35, 209-228.

Anagnostopoulos, I. (2018). Fintech and regtech: Impact on regulators and banks. Journal of Economics and Business, 100, 7-25.

Andoni, M., Robu, V., Flynn, D., Abram, S., Geach, D., Jenkins, D. & Peacock, A. (2019). Blockchain technology in the energy sector: A systematic review of challenges and opportunities. Renewable and Sustainable Energy Reviews, 100, 143-174.

B. Bilbao and V. Argentaria, “Top blockchain projects related to loans : SALT Lending - Crypto-collateral lending,” 2018.

B. V. Buterin, (2009). OffsetMapping, 1–36.

Brad, S., & Brad, E. (2015). Enhancing SWOT analysis with TRIZ-based tools to integrate systematic innovation in early task design. Procedia engineering, 131, 616-625.

C. Dannen. (2017) Introducing Ethereum and Solidity.

Catania, L., Grassi, S., & Ravazzolo, F. (2019). Forecasting cryptocurrencies under model and parameter instability. International Journal of Forecasting, 35(2), 485-501.

Chen, J., & Micali, S. (2019). Algorand: A secure and efficient distributed ledger. Theoretical Computer Science, 777, 155-183.

Ferrer-Gomila, J. L., Hinarejos, M. F., & Isern-Deyà, A. P. (2019). A fair contract signing protocol with blockchain support. Electronic Commerce Research and Applications, 36, 100869.

Glass, J. R., Kruse, G. H., & Miller, S. A. (2015). Socioeconomic considerations of the commercial weathervane scallop fishery off Alaska using SWOT analysis. Ocean & Coastal Management, 105, 154-165.

González-Carrasco, I., Jiménez-Márquez, J. L., López-Cuadrado, J. L., & Ruiz-Mezcua, B. (2019). Automatic detection of relationships between banking operations using machine learning. Information Sciences, 485, 319-346.

Humaidan, S. S. (2015). An exploratory study to determine the suitability of applying information systems using (SWOT) analysis, at administrative affairs department in power plant maintenance centre. Procedia Computer Science, 65, 787-796.


Li, J., Greenwood, D., & Kassem, M. (2019). Blockchain in the built environment and construction industry: A systematic review, conceptual models and practical use cases. Automation in Construction, 102, 288-307.

Macaulay, C. R. (2015). Capitalism's renaissance? The potential of repositioning the financial ‘meta-economy’. Futures, 68, 5-18.

Mattila, J., Naucler, C., Stahl, R., Tikkanen, M., & BÂdenlid, A. (2016). Industrial blockchain platforms: An exercise in use case development in the energy industry (No. 43). ETLA Working Papers.

Pearson, S., May, D., Leontidis, G., Swainson, M., Brewer, S., Bidaut, L., ... & Zisman, A. (2019). Are Distributed Ledger Technologies the panacea for food traceability?. Global Food Security, 20, 145-149.

Presthus, W., & O’Malley, N. O. (2017). Motivations and barriers for end-user adoption of bitcoin as digital currency. Procedia Computer Science, 121, 89-97.

Pustišek, M., & Kos, A. (2018). Approaches to front-end IoT application development for the ethereum blockchain. Procedia Computer Science, 129, 410-419.

Qiu, T., Zhang, R., & Gao, Y. (2019). Ripple vs. SWIFT: Transforming Cross Border Remittance Using Blockchain Technology. Procedia computer science, 147, 428-434.

Raschendorfer, A., Mörzinger, B., Steinberger, E., Pelzmann, P., Oswald, R., Stadler, M., & Bleicher, F. (2019). On IOTA as a potential enabler for an M2M economy in manufacturing. Procedia CIRP, 79, 379-384.

Shala, B., Trick, U., Lehmann, A., Ghita, B., & Shiaeles, S. (2019). Novel trust consensus protocol and blockchain-based trust evaluation system for m2m application services. Internet of Things, 7, 100058.

Thamrin, H., & Pamungkas, E. W. (2017). A Rule Based SWOT Analysis Application: A Case Study for Indonesian Higher Education Institution. Procedia computer science, 116, 144-150.

U. Team, “Trustworthy Peer Financing with Ultiledger Blockchain Protocol and Ecosystem,” 2018.

Unal, D., Hammoudeh, M., & Kiraz, M. S. (2020). Policy specification and verification for blockchain and smart contracts in 5G networks. ICT Express, 6(1), 43-47.

Verdian, G., Tasca, P., Paterson, C., & Mondelli, G. (2018). Quant overledger whitepaper.

Viriyasitavat, W., & Hoonsopon, D. (2019). Blockchain characteristics and consensus in modern business processes. Journal of Industrial Information Integration, 13, 32-39.

Wang, L., Shen, X., Li, J., Shao, J., & Yang, Y. (2019). Cryptographic primitives in blockchains. Journal of Network and Computer Applications, 127, 43-58.


Westerkamp, M., Victor, F., & Küpper, A. (2020). Tracing manufacturing processes using blockchain-based token compositions. Digital Communications and Networks, 6(2), 167-176.

Wood, G. (2014). Ethereum: A secure decentralised generalised transaction ledger. Ethereum project yellow paper, 151(2014), 1-32.

Yu, T., & Shen, W. (2019). Funds sharing regulation in the context of the sharing economy: Understanding the logic of China's P2P lending regulation. Computer law & security review, 35(1), 42-58.

Zhang, Y., Li, H., Hai, M., Li, J., & Li, A. (2017). Determinants of loan funded successful in online P2P Lending. Procedia computer science, 122, 896-901.

SWOT Analysis of Lending Platform from Blockchain ...

Documents